Find brands

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/idempotent/openWorld/non-destructive, so the safety profile is covered. The description adds genuinely new context beyond them: the corpus size (~3,200 brands), the nature of the returned value (slugs), and the examples of valid inputs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, zero filler, with the purpose and scale front-loaded and the usage/routing instruction second. Every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value explanation is unnecessary, and the description covers purpose, scale, and downstream use. It stops short of noting pagination behavior, but the schema already carries defaults and bounds.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so page/limit/query are already fully documented in the schema (including Persian/English examples and 'empty = all, A-Z'). The description adds no parameter detail beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Find brands by name') and the key return artifact ('with their slugs'), plus dataset scale (~3,200 brands). It also routes the agent to the siblings that consume the output, so it is distinguishable from kh_search/kh_categories without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use it: to obtain the brand slug for kh_browse / kh_filters `brands`, with concrete examples ('simple', 'cerave'). No explicit when-not or exclusion clause, so it is clear context rather than full routing rules.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.